Recognition of lines in a chalkboard
I will assume that the camera is stable (no change in position, zoom or other settings during the video recording), otherwise the task becomes markedly more complicated.

Let's say that your dataset is an array of rasters (images in array format). You mention that you want to detect events "start line" and "end line". 

One way of doing this would be to compute an approximate time derivative of your image series. For instance, take the image raster at index idx and the one right after, at index idx+1 (captured at instants $t$ and $t + \Delta t$, where $\Delta t$ is the sampling interval).

At coordinates $(i,j)$, this derivative could look something like: timeDerivative = (images[idx][j][i] - images[idx+1][j][i])/DeltaT. This is a crude estimate, and there are better ways of computing an approximate discrete derivative, but you get the idea.

Following this, you could declare a state of the recording: drawing line or not drawing line. The states, we assume are always alternating, as a teacher has to take his hand off the blackboard to draw a new line.

When a derivative with large values is detected (a region in the image goes from being black to white suddenly) and the state is "not drawing", the event "start line" is recorded and the state switches to "drawing". While a derivative with large values continues to be detected as time goes on in the vicinity of the previous spot with a large derivative, nothing changes. Once this is no longer true, the state changes to "not drawing" and the event "stop line" is recorded at the last location with a large derivative.

This is the main idea, which can be improved with:


Defining the area of the blackboard, either by hand or automatically
Thresholding the images to better isolate the chalk trace from the blackboard
Using a tracker such as a Kalman filter to know where to look next for the chalk